ESD.71 | Fall 2008 | Graduate

Engineering Systems Analysis for Design


This table provides information about both the lecture (L) and recitation (R) sessions.

Introduction to course
L1 Motivation: paradigm shift from best outcome to moving distribution of outcomes to right ESD.70J in parallel for 4 days
Part 1: basics, recognition of uncertainty, valuation fundamentals, and timing issues
Conventional valuation and recognition of uncertainty

Discounted cash flow and present value

Criteria for valuation

R1 Valuation methods and discussion for uncertainty exercise  
L3 Uncertainty recognition  

Choice of discount rate

Opportunity cost, weighted average cost of capital, capital asset pricing model

Application Portfolio 1 due: Topic definition
R2 Discussion of choice of discount rate and production functions  
Timing of development
Basic issue: build now or later?

Asphalt vs. concrete highways

Basic system model: production function, economies of scale

L6 Optimum expansion size deterministic case  
R3 Exercises on production functions and economies of scale  

Determining economies of scale from cost function

Constrained optimization and marginal analysis


Sources of flexibility

“On” systems-timing

“In” systems-timing and function

Case examples

Application Portfolio 2 due: Defining uncertainties

Discussion of flexibility in application portfolio

Review of probability determination from data and Bayesian analysis

Part 2: uncertainty modeling and flexibility valuation methods
Decision analysis
L9 Uncertainty assessment  

Primitive models

Introduction to decision analysis

R5 Decision analysis practice  

Practical issues

Solutions by “folding back”

Flaw of averages

Application Portfolio 3 due: Flexibility identification

Distribution of outcomes for decision analysis

Value at risk and gain, multiple value metrics

R6 Value of information and flexibility  
L13 Benefits of waiting: value of information  
L14 Decision analysis examples: oil platform, wind energy, silicon wafer plant, Tokyo/Haneda runway Application Portfolio 4 due: Decision analysis
R7 Past midterm solutions  
L15 Mid-semester review  
L16 Midterm exam  
Lattice analysis

Lattice model to represent uncertainty

Regression to determine trend and variability (μ and σ)

R8 Review of midterm and of regression analysis  
L18 Dynamic programming: systematic solution by “folding back”  
R9 Dynamic programming and valuation of lattice model  

Valuation of lattice by dynamic programming

Satellite case study


Combining lattice and decision analysis

Case studies: aqua line tunnel

Application Portfolio 5 due: Lattice analysis of evolution of a major uncertainty
L21 Conceptual valuation and application Application Portfolio 6 due: Decision analysis using lattice
R10 Advice on application portfolios  
L22 Comparing decision analysis and lattice analysis  

Definition and analysis of “hotspots” using change propagation analysis

Path dependency

Comments on draft application portfolio

Case studies: car platforms, hydroelectric dam, mini unmanned aerial vehicle

Draft of complete portfolio due
L24 Perspective on flexibility in design and real options analysis (Part 1) Complete revised portfolio due
L25 Perspective on flexibility in design and real options analysis (Part 2)  
L26 Review for final exam